Mobile data transmission and data services are constantly making progress. With the increasing usage of mobile communication, network organization and optimization is becoming more and more important. Also, in this context self organizing networks (SON) are being investigated, e.g. in the framework of LTE™ or LTE™-A.
Insofar, the present invention relates in particular but without limitation to mobile communications, for example to environments under WCDMA, LTE™ (Long Term Evolution) or LTE™-A (LTE™ Advanced), UMTS (Universal Mobile Telecommunication System), 3GPP (3rd Generation Partnership Project) or any other communication scenario, potentially standardized by ETSI (European Telecommunication Standards Institute) and/or other local or regional standardization bodies e.g. NGMN (Next Generation Mobile Networks), and can advantageously be implemented as or in chipsets, or modules, or units, or apparatuses of devices (e.g. network entities such as a transceiver device also known as base station, or NodeB, or evolved NodeB eNB, or e.g. a mobility management entity MME) forming part of those networks.
More particularly, the present invention relates to those apparatuses/units of devices or network entities that are applied in such communication networks for the purposes of self organization and network optimization of those networks, e.g. known as SON networks.
With the evolution of LTE™ system, future cellular networks will become more and more complex, various and huge. For network operators, along with the uses of new technologies, how to reduce network infrastructure costs and operating expenses is a big challenge. So NGMN (Next Generation Mobile Networks) and 3GPP proposed the Self-Organizing Network (SON) technology, and standardized it in at least the LTE™ system.
Self-configuring and Self-optimizing are two main parts of LTE™ SON, wherein the related use cases and solutions are defined e.g. in 3GPP LTE™ TR 36.902 Release 9 (TR=Technical Report).
Self-configuring focuses on automatically installing software (such as control code portions), on configuring wireless parameters and (other) transmission parameters, and on detecting and finding neighbors (neighbor cells) and on managing relations when such system is being constructed or being setup.
Self-optimizing focuses on an adaptive adjustment of parameters according to measurement results from network devices and/or terminals within the network when the system is running or in operation. The adjustment should be within the scope defined by operators, thereby achieving the network performance optimization purposes.
For example, 3GPP in 2009 determined the objectives of SON in LTE Release 9, and then gradually completed related programs and standards on Mobility Robustness Optimization (MRO), dynamic load balancing optimization, and Random Access Channel (RACH) optimization.
Robustness in mobility requires sound handover decisions for a terminal (e.g. user equipment UE or other wireless terminal such as a smartphone or laptop) moving in a wireless, e.g. typically cellular, network environment.
A complete handover (HO) procedure can typically be divided into five parts: Measurement Control, Measurements Report, Handover Preparation, Handover Decision, and Handover Completion.
In mobile network, handover (HO) prediction and decision is a necessary, important and complex part, and if HO parameters are set right or not, this will directly impact not only a user's experience but also system performance. In 2G/3G (2nd Generation/3rd Generation) systems, manual setting of HO parameters is a time consuming task which does not achieve a too high robustness, thus a rather low robust way.
So, in e.g. 3GPP LTE™ TR 36.902 R9, Mobility Robustness Optimization (MRO) is defined to resolve the issue through self-configuring and self-optimizing method.
Currently, most of solutions on HO parameters optimization are cell-level based. For example, a network transceiver device such as an evolved NodeB (eNB) optimizes parameters known as “time to trigger”, TTT, hysteresis, hys, according to some algorithms and HO results, and the optimized parameters are applied for all users in the cell.
Because of the differences of users' mobility characteristics, those shared or cell-wide applied HO parameter are not so precise for each user, thus resulting in a reduced service quality for some users e.g. due to HO failure.
Along with the increase of cells and more and more complexity of wireless environments, the cell-level based HO parameters optimization will become powerless, and will cause some unnecessary HOs and occurrences of too late/too early HOs,
Some papers focus on studying user-level based HO optimization. Those can be divided to two categories: user HO history based method and user location based method. These algorithms just provide some ways on how to identify a user's (past or current) route/mobility pattern.
There are also some MRO algorithms dealing with HO parameter optimization, but those are merely targeted to cell-level solutions.
Thus, there is still a need to further improve such systems.